Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

Fractional Order Proportional Integral Derivative Controller Design and Simulation for Bioengineering Systems

This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order mathematical model of bioengineering systems. The main contents include the design of FOPID controller and the simulation for bioengineering systems. The simulation results show that the tuning method of fractional order system based on the FOPID controller outperforms the fractional order system based on Fractional Order Proportional Integral( FOPI) controller. As it can enhance control character and improve the robustness of the system.

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

Fuzzy PID control system for hose pulse experiment based on LabVIEW

The hose pulse testing bench generally uses electro-hydraulic servo system. It occupies little space, tracks signals fast and has simple structure, and therefore it is widely used in industrial control field. However, there are lots of problems such as little accuracy and instability caused by slow response of hydraulic and various interference factors. Simple proportional integra- tion derivatiation （PID） control method of traditional pulse bench is simple in principle, but it is difficult in parameter adjust- ment. According to the special requirements of the control system, a PID method based on fuzzy control is proposed in the pa- per. This method not only retains the advantages of the conventional control system, but also ameliorates the drawbacks of parameter uncertainty, instability and lag. It has been testified that the method is practicable and can improve the precision and adaptation.

Parallel Fuzzy P+Fuzzy I+Fuzzy D Controller:Design and Performance Evaluation

In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） controller. It preserves the linear structure of a conventional parallel PID controller, with analytical formulas. The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller. Computer simulations are performed to evaluate the performance of the FP＋FI＋FD controller for setpoint tracking and load-disturbance rejection for some complex processes, such as first- and second-order processes with delay, inverse response process with and without delay and higher order processes. Also, the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve. The simulation and real time control is done using National InstrumentTM hardware and software （LabVIEWTM）. The response of the FP＋FI＋FD controller is compared with the conventional parallel PID controller, tuned with the Ziegler-Nichols （Z-H） and /~strSm- H^gglund （A-H） tuning technique. It is observed that the FP＋FI＋FD controller performed much better than the conventional PI/PID controller. Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP＋FI＋FD controller.

Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-Control for Intelligent Vehicles

Intelligent vehicles can effectively improve traffic congestion and road traffic safety.Adaptive cruise followingcontrol(ACFC)is a vital part of intelligent vehicles.In this paper,a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model,type-2 fuzzy control,feedforward+fuzzy proportion integration(PI)feedback(F+FPIF)control,and inverse longitudinal dynamics model of vehicles.Firstly,a traditional variable time headway model is improved considering the acceleration of the lead car.Secondly,an interval type-2 fuzzy logic controller(IT2 FLC)is designed for the upper structure of the ACFC system to simulate the driver's operating habits.To reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration,the control strategy of F+FPIF is given for the lower control structure.Thirdly,the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method(no lower controller for tracking desired acceleration)separately.Meanwhile,the proportion integration differentiation(PID),linear quadratic regulator(LQR),subsection function control(SFC)and type-1 fuzzy logic control(T1 FLC)are respectively compared with the IT2 FLC in control performance under different scenes.Finally,the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.

Performance analysis of semi-active cab’s hydraulic system of the vibratory roller using optimal fuzzy-PID control

In order to evaluate the performance of semi-active cab’s hydraulic mounts(SHM)of the off-road vibratory roller with the optimal fuzzy-PID(proportional integral derivative)control,a nonlinear dynamic model of the vehicle interacting with off-road terrains is established based on Matlab/Simulink software.The weighted root-mean-square(RMS)acceleration responses of the driver’s seat heave and the cab’s pitch angle are chosen as objective functions.The SHM is then optimized and analyzed via the optimal fuzzy-PID control under different operation conditions.The simulations results show that the driver’s ride comfort and the cab shaking are greatly affected by the off-road terrains under various operating conditions of the vehicle,especially at the speed from 8 to 12 km/h on a very poor terrain surface of Grenville soil ground under the vehicle travelling.With SHM using the optimal fuzzy-PID control,the driver’s ride comfort and the cab shaking are clearly improved under various operation conditions of the vehicle,particularly at the speed from 6 to 7 km/h of the vehicle traveling.

PID-Based Bit Allocation Strategy for Asymmetric Stereoscopic Video Coding with Fuzzy Quality Controller

Asymmetric stereoscopic video coding can take advantage of binocular suppression in human vision by representing one of the two views in lower quality.This paper proposes a bit allocation strategy for asymmetric stereoscopic video coding.In order to improve the accuracy of bit allocation and rate control in the left view,a proportionalintegral-derivative controller is adopted.Meanwhile,to control the quality fluctuation between consecutive frames of the left view,a quality controller is adopted.Besides,a fuzzy controller is proposed to control the variation in quality between the left and right views by comparing the PSNR disparity of two views with a fixed threshold,which is used to quantize the binocular psycho-visual redundancy and adjust the quantization parameter (QP) of the right view correspondingly.The proposed algorithm has been implemented in H.264/AVC video codec,and the experimental results show its effectiveness in rate control while keeping a good quality for the left view,and fewer bits are allocated for the right view so that the overall bit rate is saved by 7.2% at most without the loss of subjective visual quality for stereoscopic video.

A Novel Asymmetric Three-Phase Cascaded 21 Level Inverter Fed Induction Motor Using Multicarrier PWM with PI and Fuzzy Controller

Multilevel inverters are gaining popularity in high power applications. This paper proposes a new ladder type structure of cascaded three-phase multilevel inverter with reduced number of power semiconductor devices which is used to drive the induction motor. The ultimate aim of the paper is to produce multiple output levels with minimum number of semiconductor devices. This paper uses only 11 switches along with 3 diodes and 4 asymmetrical sources to produce an output voltage of 21 levels. The modulation technique plays a major role in commutation of the switches. Here we implement the multicarrier level shifting pulse width modulation technique to produce the commutation signals for the inverter. The proposed multilevel inverter is used to drive the three-phase induction motor. The mathematical modeling of three-phase induction motor is done using Simulink. Furthermore the PI and fuzzy logic controllers are also used to produce the reference waveform of the level shifting technique which in turn produces the commutation signals of the proposed multilevel converter. The controllers are used to control the speed of the induction motor. The effectiveness of the proposed system is proved with the help of simulation. The simulation is performed in MATLAB/Simulink. From the simulation results, it shows that the proposed multilevel inverter works properly to generate the multilevel output waveform with minimum number of semiconductor devices. The PI and fuzzy logic controller performances are evaluated using the results which indicate that with the help of controllers the harmonics has been reduced and the speed control of induction motor is achieved under different loading conditions.

基于STM32的智能航行系统设计

为解决航行器智能确定航向并航行的问题,本文采取模块化的思想设计了一款基于STM32的红外导引的智能航行控制系统。该智能航行系统利用红外接收模块进行红外导引信号的接收,采取线性加权法进行航向与导引信号之间的偏离角确定,利用比例-积分-微分(proportion-integration-differentiation,PID)控制算法对控制舵机转角的脉冲宽度调制(pulse width modulation,PWM)信号的占空比进行确定,从而对螺旋桨的转速与舵桨的转角进行可靠控制。根据水池测试结果,该智能航行控制系统能够对红外接收信号进行快速处理,在保持较高航速的条件下进行可靠的航行控制。

盾构掘进姿态控制技术研究现状与未来展望

为系统地分析我国盾构掘进姿态控制技术的研究进展,基于知网检索到的32篇相关文献,总结盾构掘进姿态的主要表征参数和影响因素,并以盾构液压推进系统为例论述其控制原理。同时,结合盾构姿态智能控制的部分案例,总结PID控制、自适应控制、模糊控制、基于神经网络的控制和基于智能算法的控制等技术的优劣势及应用场景。基于以上分析,对盾构姿态控制技术的发展方向进行展望。研究发现:1)盾构掘进姿态的影响因素主要包括几何参数、地层参数和盾构掘进参数。2)由于盾构推进系统需要同时完成盾构向前推进和姿态调整等复杂任务,因此该系统的参数对盾构姿态有着很大的影响,是姿态控制的关键因素之一。3)相较于传统PID控制方法,智能控制方法与PID控制的结合可以提高系统的响应速度、精度、适应能力和鲁棒性。4)未来研究可以围绕基于多源数据融合的控制算法、构建数据-机制混合驱动的控制技术以及加强控制技术在实际工程中的实用性等方面展开,实现更精准、更高效的盾构掘进姿态控制。

基于强化学习的柴油机调速算法研究

为了更好地调节柴油机转速,提出一种强化学习–比例积分微分(proportional integral derivative, PID)控制器,并应用到了柴油机转速控制中。基于连续动作空间的柔性动作–评价(soft actor-critic, SAC)算法,结合连续型PID控制器,设计了一种强化学习–PID控制器,可代替传统PID控制的转速环。优化设计了基于演员–评论家(actor-critic)框架的输入输出和奖励函数以匹配柴油机特性,采用随机动作增加寻优效率,形成SAC-PID控制柴油机转速的网络交互结构,达到快速调整转速,减小稳定时间的效果。构建了以柴油机D6114为原型机的MATLAB/Simulink平均值模型,并利用试验数据验证了仿真模型的有效性。利用平均值模型,仿真验证了该控制算法效果。经过仿真验证本算法使柴油机转速响应曲线超调量更小,响应时间更快,鲁棒性更强,SAC-PID控制负载瞬态调速率和稳定时间均已达到1级精度指标。仿真对比验证了SAC算法的联合控制效果,结果表明其较其他算法更佳。

风扰下变质量四旋翼轨迹跟踪控制

针对存在风扰和变质量负载扰动的四旋翼无人机轨迹跟踪控制问题,提出了一种基于降阶广义比例积分观测器的动态面模糊滑模控制方法。首先,建立含风扰和变质量负载扰动的四旋翼无人机系统模型;其次,结合四旋翼无人机系统模型设计降阶广义比例积分观测器估计外界风扰;再次,设计动态面滑模控制器,并采用模糊控制模糊化切换增益,以此有效地抑制抖振;然后,通过Lyapunov稳定性证明四旋翼无人机系统的稳定性;最后,通过Matlab-Simulink进行3种控制方法的仿真比较。仿真结果表明,当存在风扰和变质量负载扰动时,该控制方法抗风扰能力更强,稳定性更好,位姿跟踪精度更高。

低附着路况条件下车辆横向稳定性控制

针对在冰雪环境下车辆横向稳定控制,为解决在低附着、分布不均的路面情况下车辆对参考轨迹的稳定跟踪问题,设计了基于神经网络调节的模糊PID(Proportional-Integral-Differential)制器,以及基于线性化车辆模型的模型预测控制(MPC:Model Predictive Controll)。以路面附着系数及车辆速度作为输入构建BP(Back-Propagation)神经网络,输出调节系数优化模糊PID控制器控制性能;设计了十自由度模型表征车辆在冰雪环境下的动力学特性,使用MPC实现车辆横向稳定控制。使用CarSim/Simulink进行联合仿真实验,结果表明该控制器能显著提高车辆轨迹跟踪性能。

边缘计算在隧道车道控制中的应用与优化

主干公路中的隧道车道设计容量通常有限,当车流量超过道路的承载能力时容易导致拥堵。文章针对隧道中潮汐车道管理存在的问题,提出一种基于边缘计算的车道控制系统。首先,系统构建复杂的边缘节点,包括感知模块、通信模块、决策与控制模块等,实现拥堵时段的潮汐车道控制。其次,系统中的边缘节点以网络摄像头、工业计算机和车道控制器为基础,构建一个紧密合作的系统,充分发挥边缘计算的优势。最后,针对交通流量的变化,文章引入自适应车道控制策略,通过比例-积分-微分(Proportional-Integral-Derivative,PID)控制器动态调整相位时长,以提高车流通行效率。

热风洞温度系统的无模型自适应级联控制

热风洞能够为高温热电偶动态标定和航空发动机叶片热强度测试等应用场景提供均匀且稳定的温度场,如何对热风洞所产生的热气流进行宽温范围的温度控制是一个难点。为此,建立了热风洞燃油流量和燃烧室温度的数学模型;设计了一种内环为增量式比例积分微分(PID)和外环为无模型自适应控制(MFAC)的级联控制方法,增量式PID控制器控制燃油流量,MFAC控制器控制燃烧室温度,实现了对燃烧室温度的有效控制;进行了不同目标温度的数值模拟和试验研究,并与FuzzyPID-PID级联控制方案和传统的级联PID控制方案进行了对比测试。试验结果确认了所提控制方案的可行性与优越性。

基于预期动态方程的含高比例可再生能源孤岛运行微电网负荷频率控制

针对高比例可再生能源并入微电网带来的负荷频率控制问题,提出基于预期动态方程的比例-积分-微分(PID)控制策略.在分析微电网负荷频率控制模型和控制难点的基础上,设计基于预期动态方程的PID控制策略,采用单一变量法分析控制器参数对控制效果的影响,总结了简单、实用的参数整定流程,并在微电网负荷频率控制系统中应用.在不同工况下与多种控制器进行仿真对比,结果表明:所提控制策略能够在保证鲁棒性的前提下取得最佳控制效果,展现出很高的工程应用价值.

面向溺水救援机器人平稳跟踪的模糊比例微分控制视觉伺服方案

针对溺水救援机器人的平稳跟踪需求,提出一种基于模糊比例微分控制的视觉伺服方案,通过场馆顶部安装的俯视摄像头获取机器人的坐标位置,使用虚拟导航线设计动态行走路径,计算偏移方向、偏移角并制定转弯规则;利用三角隶属度函数制定模糊比例、微分控制规则表,根据2种规则表中的比例、微分系数分别控制机器人的偏移角、距离偏移量及其变化率,实现机器人的跟踪与避障的平稳性调整;机器人采用核相关滤波跟踪算法对溺水人员进行跟踪,在溺水人员位置变化时调整运动方向,依靠实时、稳定的声呐信息设置偏移角,实现避障功能;对所提出的方案在先锋P3DX型机器人上进行实验验证。结果表明:机器人能及时应对目标变化,没有跟错、跟丢现象;在不同工况时的横滚角均小于1°,避障率达到100%,能够快速、稳定、准确地到达目标位置,达到溺水救援机器人的前期应用要求。

CONTROL OF ROBOT DRIVEN BY MULTIPLE ULTRASONIC MOTORS BASED ON ROBUST PARAMETER DESIGN

An ultrasonic motor （USM） is difficlt to be mathematically described because of its complex energy conversion and nonlinear parameters from increasing temperature and changing operating conditions. To achieve good performance of a three-joint robot directly driven by USM, according to the operating characteristics of USM, a new position-velocity feedback control strategy is proposed. In the control strategy, there are a total of 18 controller gains to he tuned. Through a series of ＂Design of Experiments＂ by the robust parameter design, an optimal and robust set of proportional integral derivative （PID） controller gains is obtained. Results show that the control strategy can achieve the best performance of the robot and the robust parameter design is effective and convenient to USMs.

基于扩张状态观测器的无人机云台系统控制算法

针对无人机(UAV)三轴云台增稳控制中变量耦合的问题,提出一种基于扩张状态观测器(ESO)的无人机云台系统控制算法。首先,建立了无人机机载云台期望角的姿态解算算法模型;其次,构建了无人机机载云台位置环和速度环的串级比例-积分-微分(PID)控制回路;最后,引入ESO对机载云台角速度项在线实时估计,解决角速度项由于高耦合、多外扰导致的难以直接测量的问题,并对各通道的控制输入进行补偿。实验结果表明,所提算法在无指令、有指令和综合任务场景下的角度均方根误差分别为0.2357°、0.6317°和0.9463°,与传统PID算法相比,所提算法的角度误差分别降低了69.43%、53.29%和50.43%。可见,所提算法对外界扰动的抗干扰能力更强,控制精度更高。